An Empirical Evaluation of Deep Learning for Network Anomaly Detection Academic Article

authors

• Kim, Jinoh

published proceedings

• IEEE ACCESS

author list (cited authors)

• Malaiya, R. K., Kwon, D., Suh, S. C., Kim, H., Kim, I., & Kim, J.

citation count

• 22

complete list of authors

• Malaiya, Ritesh K||Kwon, Donghwoon||Suh, Sang C||Kim, Hyunjoo||Kim, Ikkyun||Kim, Jinoh

publication date

• January 2019

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Access  Journal

keywords

• Anomaly Detection
• Deep Learning
• Learning Systems
• Network Anomaly Detection
• Neural Networks
• Performance Evaluation
• Security
• Sequence-to-sequence
• Support Vector Machines
• Traffic Analysis
• Training

Digital Object Identifier (DOI)

• 10.1109/ACCESS.2019.2943249

start page

• 140806

end page

• 140817

volume

• 7

URL

• http://dx.doi.org/10.1109/access.2019.2943249